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Big data: a key factor at the beginning of the supply chain

Big data can create huge business benefits in process industries – but for this to happen, your organization needs to understand the impact and the transformation that is needed. Jacqui Taylor, CEO of FlyingBinary, explains why people are the key for the Internet of Things (IoT).

“Material handling is a key factor in process industries, such as steel or automotive, because it is at the beginning of the supply chain. In order to reap the benefits of IoT, you first have to plant the data seed”, Jacqui Taylor begins.

In order to make the best use of IoT in a sector like this, it is important to understand your organization and how ready it is to embrace IoT. In order to gain the value from IoT, it is important to understand data. How data literate is your organization? How mature are you at handling data and driving the value from data? These are important issues to consider.

“Data is a key resource, but having data doesn’t get you anywhere. Lots of companies will tell you that they’re drowning in data, but they have no information. What you’re doing with the data is the key”.

One component of that is sensor data and the immediacy it allows, for example by creating live data streams and basing key decisions on that data. This change is essential to reap the benefits for material handling and the transformation of the supply chain, because it helps in understanding the heartbeat of processes and contains the key to delivering the efficiencies of real-time data streams.

Big data technology can also deliver evidence of the challenges that are currently unknown in an organization, it will highlight the key areas of focus to gain maximum benefits for moving into this new arena. This allows a board to change strategy and to drive innovation, Taylor says.

Articulating the art of the possible

Big data also starts to transform the organization.

“People are the key. You have an organization that is set up to do one thing, and that legacy has set up the current supply chain, however people understand the inefficiencies of this and with data can use their domain knowledge to spot the opportunities for change, once they have the data. Ultimately sensors and the changes for IoT need to be embedded across the supply chain, but you can’t change all of this at once, but you can’t ignore it either, data allows you to select the best area of focus”, Taylor says.

To create the change that is needed, people need an understanding of which direction to take and why. This comes down to changing mindsets and being able to articulate what is possible to achieve, with the help of big data technology.

“Data is a key resource, but having data doesn’t get you anywhere. Lots of companies will tell you that they’re drowning in data, but they have no information. What you’re doing with the data is the key”

“You choose wisely where you start and what you do, and you do it with confidence. It’s not only about the process in the organization itself and what you’re creating with materials, but also your impact on the ongoing supply chain. The technology on its own is there, but the question is what can do with it and how you’re going to explain the impact and the transformation that is needed in the organization. So it’s a strategic approach more than something that is missing”.

Change can of course confuse or scare people. Therefore Taylor suggests starting with a pilot plan to create an understanding of what is possible. Looking at a specific project or proof of concept, the understanding then goes into the organization of the challenge that has been solved and the opportunity that exists.

“If you enable people to understand, then they will take those steps – not everybody, you do need the right people to make this transition. If we’re going to change something, you need to understand why. But if we don’t understand what the problem we’re solving is, change won’t be transformative”.

Moving towards results

If you understood what the possibilities were, and the competitive advantages this brings, organizations would rush to do them. To put this in context, Hollywood current invests in a movie with a return of x 3 for every dollar invested. Our clients have evidenced that for every £1 invested in this approach the return is between £2 and £40. Taylor explains.

“Officially, now we’re in a world where we have done digital, and the industrial internet is next. Those people who are going to lead this whole concept will rise above the competition in all sectors by having game changing access to and understanding of the data for the industrial internet. You can’t underestimate the importance material handling will have in this, because it is the beginning of the supply chain. The companies that are involved in this sector have a huge opportunity to make a difference”.

According to Taylor, using big data technology to construct the supply chain in a new way allows you to put your focus on the customer in a way that has never been possible before.

“For example, manufacturing is a global business, and with IoT and Big Data across the supply chain it is possible to understand the bottlenecks and opportunities which exist for any product being manufactured anywhere in the world. Using data from sensors through the production process would mean any delay in the delivery components or raw materials, or an extreme weather event would enable supply chain data to be re configured, allowing pre-production and production processes to be moved to new schedules, “inflight“.

“Whilst there is an opportunity to use big data across many sectors such as construction and advanced manufacturing the fact that you can say, as a material handler, what’s possible and what’s not, is because you’re at the beginning of the supply chain, the rest of the supply chain can’t do that. This makes a material handling business responsive, and it allows for big data to really start delivering on its promise for organizations ready to embrace this paradigm shift”.

The downside of this new approach is that it means using different technologies than those the organization is familiar with. This is not necessarily a problem – it just shows that there needs to be a shared understanding in the organization that in order to get to the benefits, you need big data technologies, Taylor says.

And this, again, brings the people into the spotlight.

Jacqui Taylor is the founder and CEO of FlyingBinary, a web science company that changes the world with data.

Image credit: © morganimation – Fotolia.com

Interview w/ Jacqui Taylor

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How to manage the abundance of information

From a scarce commodity to abundance, information has always posed challenges to companies. Maija Nikula, Head of Enterprise Architecture, explains how the industrial internet may bring answers to some well-known problems companies are struggling with today.

Information has always posed a challenge to companies. Some years ago, information was a scarce commodity. Today, there is an abundance of information. In fact, we’re surrounded with so much information that it makes focusing on the right things more difficult than before. That’s quite a paradox.

So how should we go about tackling this issue? The basic principles of the industrial internet are based on the following questions: how to collect information, how to utilize the information collected and how to find the best competences? Basically, the industrial internet tries to solve the problematic of using and utilizing information.

Industrial internet will have an effect on information handling in every area of business. It’s not a concern for the CIO alone. It’s a concern for sales, marketing and finance – and, if the information is used wisely, it will have a positive effect on every area of business. Recent developments in digitalization have equipped us with tools and information which could help us to generate new sales leads and new innovations for marketing as well as make finance functions more efficient. Now, we just need to learn how to use these opportunities.

Enterprise architecture will play an important role in building the platform for the growth of the industrial internet in companies. But how does the industrial internet change enterprise architecture?

Tackling the three V’s of information

With industrial internet and big data, the amount and the structure of data have changed. This comes down to the three V’s of information: Volume, Velocity and Variety. All of these have increased with big data, bringing both challenges and possibilities to utilizing the information.

Sensor data, for example, has increased the volume of information. But the data also needs to be interpreted: when a device gives signals through the sensors to indicate that the device is wearing out, it’s not enough to determine that the device requires maintenance sometime in the future. What is needed instead is the capacity for real-time monitoring and the know-how to pin-point the key findings and set actions based on them.

This brings us to velocity. Data acquired should lead to rapid actions taken in order to get maintenance over immediately. It requires not only analytic tools but also the integration of those tools to ensure real-time analysis.

The technology today enables faster decision making, but it also requires the ability to change existing operating models faster when required.

In event stream processing, the data is not just stored to a database, but analyzed when transferred from one place to another and necessary actions are taken based on that analysis. From an enterprise architect’s point of view, event stream processing is a world of its own, a whole new technology.

This is a challenge of data analytics as a whole: analyses are done constantly and the tools exist, but whether a company is able to take the right actions, that’s another question.

To be able to analyze the growing variety of information, we need to consider what internal resources are needed, partly from a technology point of view but most of all from an information analysis point of view.

From a technical point of view, in order to do this, companies should be able to make changes into existing systems as flexibly as possible. But there is also a need for people who have the competence to figure out how the business should be changed when data acquired suggests that it is needed.

That is why the process of using the analytic tools, integrating them and invocating this information is also a question of change management. The technology today enables faster decision making, but it also requires the ability to change existing operating models faster when required. The changes vary in size, but the key is the willingness to make changes and the ability to make them fast.

Image credit: Verticalarray / Shutterstock.com

Maija Nikula
Maija Nikula works as the Head of Enterprise Architecture at Konecranes

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Tackling the bottlenecks of information flow with MES

In a factory environment, information can often cause a bottleneck in productivity. Mikko Mäki-Rahkola, Development Manager IT at Pesmel, an internal logistics, storing and packing solutions supplier, explains how Manufacturing Execution Systems (MES) increase the information flow in a factory environment, thereby improving the overall productivity.

”When you aim to improve the efficiency of a factory environment, hardware can get you to a certain point. But after that point it is intelligence that counts. The bottlenecks of efficiency and safety essentially come from information: how well the production planning has been made, how optimally you are using your stock and how much stuff is kept in stock in the first place”, Mäki-Rahkola explains.

The importance of software in factories has increased for several decades. Software has become more and more efficient, and after the arrival of the internet, different organizations have been able communicate to one another more easily. This, in turn, has made transferring information between different devices easier.

According to Mäki-Rahkola, when it comes to discussing business improvement, technology can sometimes steal the spotlight. Nevertheless, in todays factories there are still a lot of people delivering the actual information and making decisions about what to do and how to do it. In conversations regarding the industrial internet, information is often understood as information derived from devices as well as larger amounts of data created with the help of sensors and an internet connection. The utilization of capabilities provided by the industrial internet is, as Mäki-Rahkola points out, still in its early stages. At the same time it should be noted how many factories are lagging on performance by using very traditional methods.

”At the factory floor level, Excel files and paper sheets are still widely in use. For example, in order to find out the origin of a single consignment, you have to combine many different pieces of information. I believe that in the future, both the devices in a factory and the data for their operation will be managed by a single intelligent platform.”

Mäki-Rahkola thinks that MOM (Manufacturing Operation Management) systems will be the next big thing in manufacturing, following the large scale implementation wave of ERP (Enterprise Resource Planning) systems and past MES (Manufacturing Execution System) experiments. In addition to traditional MES functionalities such as production execution, data collection and device control, MOM systems also include stock control, quality control and maintenance control functions. These systems make it possible to manage the production processes so that production plans can be made accurately according to demand and the current stock, all the while streamlining the whole process.

Traceability is essential

One reason for companies to renew their manufacturing execution systems is better information processing and data acquisition leading to improved traceability. Mäki-Rahkola says that there are still surprisingly many factories where managers do not know the amount of goods being produced in the factory on a given day.

In various industries today the pressure to improve traceability is huge.

In addition to traditional MES functionalities such as production execution, data collection and device control, MOM systems also include stock control, quality control and maintenance control functions

“For example, if you need to find out why a customer has gotten food poisoning or why a component in an airplane is damaged for no apparent reason, the tracing has to go all the way back to the individual ingredients of the product or to the manufacturing process of the component in order to find out if quality control during the manufacturing process has been sufficient. The amount of information is massive and the need to track down this information has become very time-sensitive. This is not possible with traditional methods.”

Methods used at the factory floor level can, however, be very traditional. Mäki-Rahkola gives an example about a case where a team of nearly ten people was running a factory’s production planning. Even though the company was using ERP and modern, automated equipment, there was still an information bottleneck.

The production plan was in practice realized as dozens of device-specific and production line-specific Excel files. If the company received an urgent new customer order, the production manager looked at the main schedule Excel file to see which orders had to be prioritized and which orders could be delayed. The team would then identify all of the orders and the planning team would recalculate them again. This requires a massive reprocessing of Excel files where tables would be manually updated to make sure that everything matches. And, as we all know, with manual updates there is always a chance of miscalculations and errors in addition to the manual work and time delays.

With modern manufacturing execution systems, this kind of manual information handling and optimization can be automated. A single person can place the order in the main production plan and the software can re-calculate and re-optimize thousands of other orders and their new constraints, all within seconds.

Adopting a labor-intensive way of doing things is still common, and there are historical reasons to explain this. When labor costs were low, it was common to think that material handling can be made faster with the addition of more truck drivers, for example. Now, these same needs are repeating in information handling, and the management of increasing information flows has traditionally been done by increasing the number of people managing the information.

When it comes to information handling, companies have started waking up to automation as well. With labor costs and the number of orders as well as the amount of necessary information in each process increasing, it is not possible to become more effective solely by hiring new people anymore, Mäki-Rahkola sums up.

Mikko Mäki-Rahkola works as Development Manager IT at Pesmel

Image credit: phipatbig/Shutterstock.com

Interview w/ Mikko Mäki-Rahkola

4 Comments

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  • Sivert Westergård 14.04.2015 09:42

    Hello Mikko!

    Good article showing new possibilities to increase productivity fulfilling simultaneously new demands for the future using industrial internet!

    • Mikko Mäki-Rahkola 14.04.2015 13:09

      Thanks Sivert!

  • Dr.Amod Tootla 09.04.2015 20:36

    I am a cancer surgeon. How can the new tech. be applied in a hospital setting-avoiding errors and become more efficient?

    Thanks.
    Dr.Amod Tootla

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IoT and cloud technology are seen as key elements in creating a secure data environment

As IoT requires a more open architecture, some users are skeptical about the platforms’ ability to maintain the integrity of their data. According to the new analysis from Frost & Sullivan called Internet of Things (IoT) – Disruptive Opportunities in Key Sectors, several standardization bodies are working towards addressing the issue of device interoperability so that they could answer to users’ demands for secure environment. “The huge pressure on the network for connectivity with multiple devices could lead to a new artificial intelligent cognitive architecture for managing data network”, says Technical Insights Industry Analyst Swapnadeek Nayak. Nanotechnology and smart sensors are also seen as valuable tools for enhancing privacy and network security.

Read more of how IoT can enhance privacy in an open architecture at http://en.prnasia.com/story/116727-0.shtml

Image credit: Tatiana Popova/Shutterstock.com

Via PR Newswire

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This is why M2M communication is critical for factories

System connections at every level of factory communications are emerging as critical elements in IoT implementation. This Control Engineering article predicts that in 2015 there will be a trend for seamless integration of secure server into the control software suite including every push-button, servo drive, energy monitor, vision camera, accelerometer and more. Little by little the safety focus will move from hardwired safety towards networked safety. Safe motion enables continuous operation and significant cost savings, which are high on the agenda for every manufacturing manager.

Explore 10 of the near future trends in manufacturing automation at: http://www.controleng.com/single-article/what-does-the-internet-of-things-mean-to-people-who-make-things/21f0adfae8f2cd6681b168aaeb7a951f.html

Image credit: branislavpudar/Shutterstock.com

Via Control Engineering

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